Noisy unstructured text data is ubiquitous in real-world communications. Text produced by processing signals intended for human use such as printed/handwritten documents, spontaneous speech, and camera-captured images, are prime examples. ICR/OCR error rates on paper documents can range widely from 2-3% for clean inputs to 50% or higher depending on the quality of the page image, the complexity of the layout, aspects of the typography, etc. Individual variability in handwriting make this a particularly difficult form of input and error rates here are often substantially higher than for machine print text. Telephonic conversations between call center agents and customers often see 30-40% word error rates, even using state-of-the-art ASR techniques. In spite of the tremendous challenges such data presents, it is pervasive in applications of interest to corporations and government organizations.

Recognition errors are not the sole source of noise; natural language and the creative ways that humans use it can create problems for computational techniques. Electronic text from the Internet (emails, message boards, newsgroups, blogs, wikis, chat logs and Web pages), contact centers (customer complaints, emails, call transcriptions, message summaries), and mobile phones (text messages) is often noisy, containing spelling errors, abbreviations, non-standard words, false starts, repetitions, missing punctuation, missing case information, and pause-filling words such as “um” and “uh” in the case of spoken conversations.

The Third Workshop on Analytics for Noisy Unstructured Text Data (AND-09) is devoted to issues arising from the need to contend with noisy inputs, the impact noise can have on downstream applications, and the demands it places on document analysis.  AND 2009 will build on two previous successful AND workshops held in 2007 (in conjunction with the 20th International Joint Conference on Artificial Intelligence) and in 2008 (in conjunction with the 31st Annual International ACM SIGIR Conference). AND 2008 proceedings are available in ACM Digital Library (http://portaltest.acm.org/toc.cfm?id=1390749&type=proceeding&coll=portal&dl=ACM). Selected papers from AND 2007 was published in a special issue of International Journal of Document Analysis and Recognition (IJDAR) and selected papers from AND 2008 will appear in IJDAR at a future date. For AND 2009 as well, the on-line proceedings will be published by ACM and selected papers will be invited to be a part of a special issue published by IJDAR.